Overview

Dataset statistics

Number of variables7
Number of observations2425
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory151.6 KiB
Average record size in memory64.0 B

Variable types

DateTime1
TimeSeries5
Numeric1

Timeseries statistics

Number of series5
Time series length2425
Starting point2010-01-04 00:00:00
Ending point2019-08-26 00:00:00
Period1 day, 10 hours and 51 minutes
2026-02-01T18:39:01.636096image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:01.946934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Alerts

adj close is highly overall correlated with close and 3 other fieldsHigh correlation
close is highly overall correlated with adj close and 3 other fieldsHigh correlation
high is highly overall correlated with adj close and 3 other fieldsHigh correlation
low is highly overall correlated with adj close and 3 other fieldsHigh correlation
open is highly overall correlated with adj close and 3 other fieldsHigh correlation
adj close is non stationaryNon stationary
close is non stationaryNon stationary
high is non stationaryNon stationary
low is non stationaryNon stationary
open is non stationaryNon stationary
adj close is seasonalSeasonal
close is seasonalSeasonal
high is seasonalSeasonal
low is seasonalSeasonal
open is seasonalSeasonal
Date has unique valuesUnique
volume has 32 (1.3%) zerosZeros

Reproduction

Analysis started2026-02-02 00:38:58.495276
Analysis finished2026-02-02 00:39:01.543623
Duration3.05 seconds
Software versionydata-profiling vv4.18.1
Download configurationconfig.json

Variables

Date
Date

Unique 

Distinct2425
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
Minimum2010-01-04 00:00:00
Maximum2019-08-26 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-02-01T18:39:02.068521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:02.151170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

adj close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1865
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.6791
Minimum1050.8
Maximum1888.7
Zeros0
Zeros (%)0.0%
Memory size37.9 KiB
2026-02-01T18:39:02.255070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1050.8
5-th percentile1117.46
Q11222.5
median1289.3
Q31404.6
95-th percentile1719.76
Maximum1888.7
Range837.8999
Interquartile range (IQR)182.09998

Descriptive statistics

Standard deviation180.11226
Coefficient of variation (CV)0.13424392
Kurtosis0.059891613
Mean1341.6791
Median Absolute Deviation (MAD)79.199951
Skewness0.98811718
Sum3253571.9
Variance32440.427
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3288548844
2026-02-01T18:39:02.348248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:02.647327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 14 minutes
std8 hours, 21 minutes and 10.8 seconds
2026-02-01T18:39:03.622564image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1273.6999516
 
0.2%
1313.6999515
 
0.2%
1254.3000494
 
0.2%
1293.3000494
 
0.2%
1253.8000494
 
0.2%
1324.6999514
 
0.2%
1209.5999764
 
0.2%
1251.6999514
 
0.2%
1294.6999514
 
0.2%
1290.5999764
 
0.2%
Other values (1855)2382
98.2%
ValueCountFrequency (%)
1050.8000491
< 0.1%
1052.1999511
< 0.1%
1054.1999511
< 0.1%
1056.1999511
< 0.1%
1060.0999761
< 0.1%
1060.3000491
< 0.1%
1061.6999511
< 0.1%
1062.4000241
< 0.1%
1062.9000241
< 0.1%
1063.8000491
< 0.1%
ValueCountFrequency (%)
1888.6999511
< 0.1%
1873.6999511
< 0.1%
1869.9000241
< 0.1%
1858.3000491
< 0.1%
1856.4000241
< 0.1%
1854.4000241
< 0.1%
1848.9000241
< 0.1%
1828.51
< 0.1%
1826.8000491
< 0.1%
1826.6999511
< 0.1%
2026-02-01T18:39:02.428327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1865
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.6791
Minimum1050.8
Maximum1888.7
Zeros0
Zeros (%)0.0%
Memory size37.9 KiB
2026-02-01T18:39:04.111362image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1050.8
5-th percentile1117.46
Q11222.5
median1289.3
Q31404.6
95-th percentile1719.76
Maximum1888.7
Range837.8999
Interquartile range (IQR)182.09998

Descriptive statistics

Standard deviation180.11226
Coefficient of variation (CV)0.13424392
Kurtosis0.059891613
Mean1341.6791
Median Absolute Deviation (MAD)79.199951
Skewness0.98811718
Sum3253571.9
Variance32440.427
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3288548844
2026-02-01T18:39:04.206969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:04.479795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 14 minutes
std8 hours, 21 minutes and 10.8 seconds
2026-02-01T18:39:05.439451image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1273.6999516
 
0.2%
1313.6999515
 
0.2%
1254.3000494
 
0.2%
1293.3000494
 
0.2%
1253.8000494
 
0.2%
1324.6999514
 
0.2%
1209.5999764
 
0.2%
1251.6999514
 
0.2%
1294.6999514
 
0.2%
1290.5999764
 
0.2%
Other values (1855)2382
98.2%
ValueCountFrequency (%)
1050.8000491
< 0.1%
1052.1999511
< 0.1%
1054.1999511
< 0.1%
1056.1999511
< 0.1%
1060.0999761
< 0.1%
1060.3000491
< 0.1%
1061.6999511
< 0.1%
1062.4000241
< 0.1%
1062.9000241
< 0.1%
1063.8000491
< 0.1%
ValueCountFrequency (%)
1888.6999511
< 0.1%
1873.6999511
< 0.1%
1869.9000241
< 0.1%
1858.3000491
< 0.1%
1856.4000241
< 0.1%
1854.4000241
< 0.1%
1848.9000241
< 0.1%
1828.51
< 0.1%
1826.8000491
< 0.1%
1826.6999511
< 0.1%
2026-02-01T18:39:04.290982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

high
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1873
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1348.4797
Minimum1062
Maximum1911.6
Zeros0
Zeros (%)0.0%
Memory size37.9 KiB
2026-02-01T18:39:05.914562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1062
5-th percentile1124.06
Q11226.5
median1293.7
Q31413.7
95-th percentile1728.28
Maximum1911.6
Range849.59998
Interquartile range (IQR)187.19995

Descriptive statistics

Standard deviation181.87848
Coefficient of variation (CV)0.13487669
Kurtosis0.084578926
Mean1348.4797
Median Absolute Deviation (MAD)78.899902
Skewness0.99993222
Sum3270063.2
Variance33079.78
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3364632102
2026-02-01T18:39:06.010223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:06.261493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 14 minutes
std8 hours, 21 minutes and 10.8 seconds
2026-02-01T18:39:07.027399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1320.6999515
 
0.2%
12365
 
0.2%
12924
 
0.2%
1235.1999514
 
0.2%
12474
 
0.2%
1254.54
 
0.2%
1291.5999764
 
0.2%
13124
 
0.2%
12454
 
0.2%
1292.6999514
 
0.2%
Other values (1863)2383
98.3%
ValueCountFrequency (%)
10621
< 0.1%
1064.5999761
< 0.1%
1066.1999511
< 0.1%
1068.4000241
< 0.1%
1068.51
< 0.1%
1069.51
< 0.1%
1070.1999511
< 0.1%
1070.3000491
< 0.1%
1071.51
< 0.1%
1071.9000241
< 0.1%
ValueCountFrequency (%)
1911.5999761
< 0.1%
1909.3000491
< 0.1%
18951
< 0.1%
1884.1999511
< 0.1%
1881.3000491
< 0.1%
1874.4000241
< 0.1%
1873.6999511
< 0.1%
18701
< 0.1%
1853.0999761
< 0.1%
1852.4000241
< 0.1%
2026-02-01T18:39:06.088800image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

low
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1906
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1334.5829
Minimum1045.2
Maximum1864
Zeros0
Zeros (%)0.0%
Memory size37.9 KiB
2026-02-01T18:39:07.501485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1045.2
5-th percentile1110
Q11216.2
median1284
Q31392.3
95-th percentile1708.8
Maximum1864
Range818.80005
Interquartile range (IQR)176.1001

Descriptive statistics

Standard deviation178.28514
Coefficient of variation (CV)0.13358865
Kurtosis0.040972845
Mean1334.5829
Median Absolute Deviation (MAD)78.699951
Skewness0.9765484
Sum3236363.6
Variance31785.59
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3272963622
2026-02-01T18:39:07.592865image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:07.823060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 14 minutes
std8 hours, 21 minutes and 10.8 seconds
2026-02-01T18:39:08.744470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1218.5999765
 
0.2%
1244.8000495
 
0.2%
1222.1999515
 
0.2%
12514
 
0.2%
1326.1999514
 
0.2%
12404
 
0.2%
1287.54
 
0.2%
1328.54
 
0.2%
1280.3000494
 
0.2%
1224.54
 
0.2%
Other values (1896)2382
98.2%
ValueCountFrequency (%)
1045.1999511
< 0.1%
1046.1999511
< 0.1%
1049.5999761
< 0.1%
1050.51
< 0.1%
1051.0999761
< 0.1%
1052.0999761
< 0.1%
1052.6999511
< 0.1%
1058.51
< 0.1%
1058.6999511
< 0.1%
10591
< 0.1%
ValueCountFrequency (%)
18641
< 0.1%
1858.4000241
< 0.1%
18351
< 0.1%
18301
< 0.1%
1828.5999761
< 0.1%
1824.5999761
< 0.1%
1823.6999511
< 0.1%
1814.4000241
< 0.1%
1811.4000241
< 0.1%
18091
< 0.1%
2026-02-01T18:39:07.671149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

open
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1880
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.8887
Minimum1052.2
Maximum1909
Zeros0
Zeros (%)0.0%
Memory size37.9 KiB
2026-02-01T18:39:09.242521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1052.2
5-th percentile1118.02
Q11222.6
median1289.2
Q31405.7
95-th percentile1721.28
Maximum1909
Range856.80005
Interquartile range (IQR)183.09998

Descriptive statistics

Standard deviation180.35776
Coefficient of variation (CV)0.1344059
Kurtosis0.066673429
Mean1341.8887
Median Absolute Deviation (MAD)78.799927
Skewness0.99141199
Sum3254080.1
Variance32528.921
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3439015732
2026-02-01T18:39:09.335961image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:09.609527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps503
min3 days
max5 days
mean3 days, 3 hours and 14 minutes
std8 hours, 21 minutes and 10.8 seconds
2026-02-01T18:39:10.574886image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1273.55
 
0.2%
1252.6999515
 
0.2%
1292.0999765
 
0.2%
1279.4000245
 
0.2%
1239.3000494
 
0.2%
1224.8000494
 
0.2%
1256.1999514
 
0.2%
1199.6999514
 
0.2%
1612.8000494
 
0.2%
1268.4000244
 
0.2%
Other values (1870)2381
98.2%
ValueCountFrequency (%)
1052.1999511
< 0.1%
1053.6999511
< 0.1%
1054.4000241
< 0.1%
1056.51
< 0.1%
1061.9000241
< 0.1%
10631
< 0.1%
1063.4000241
< 0.1%
10641
< 0.1%
1064.5999762
0.1%
1064.8000491
< 0.1%
ValueCountFrequency (%)
19091
< 0.1%
1886.3000491
< 0.1%
1868.9000241
< 0.1%
1868.5999761
< 0.1%
1858.0999761
< 0.1%
1852.4000241
< 0.1%
18431
< 0.1%
1839.3000491
< 0.1%
18331
< 0.1%
1830.5999761
< 0.1%
2026-02-01T18:39:09.413705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

volume
Real number (ℝ)

Zeros 

Distinct903
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5824.266
Minimum0
Maximum386334
Zeros32
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size37.9 KiB
2026-02-01T18:39:11.022537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q135
median125
Q3426
95-th percentile6982.2
Maximum386334
Range386334
Interquartile range (IQR)391

Descriptive statistics

Standard deviation30588.146
Coefficient of variation (CV)5.2518457
Kurtosis48.533645
Mean5824.266
Median Absolute Deviation (MAD)110
Skewness6.6932575
Sum14123845
Variance9.3563468 × 108
MonotonicityNot monotonic
2026-02-01T18:39:11.104650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
032
 
1.3%
2025
 
1.0%
1424
 
1.0%
723
 
0.9%
523
 
0.9%
423
 
0.9%
823
 
0.9%
2722
 
0.9%
222
 
0.9%
1021
 
0.9%
Other values (893)2187
90.2%
ValueCountFrequency (%)
032
1.3%
121
0.9%
222
0.9%
318
0.7%
423
0.9%
523
0.9%
617
0.7%
723
0.9%
823
0.9%
917
0.7%
ValueCountFrequency (%)
3863341
< 0.1%
2908891
< 0.1%
2805461
< 0.1%
2761361
< 0.1%
2754421
< 0.1%
2714571
< 0.1%
2590501
< 0.1%
2544281
< 0.1%
2471681
< 0.1%
2374971
< 0.1%

Interactions

2026-02-01T18:39:01.052420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.228544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.640707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.966818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.339120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.680496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:01.113580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.279374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.695917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.018766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.390271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.751097image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:01.176683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.333107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.746888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.071357image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.450614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.811426image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:01.240312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.384637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.799623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.126119image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.506105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.861611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:01.302103image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.450333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.850374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.179186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.556191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.933007image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:01.366802image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.543094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:38:59.902022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.254686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.618805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:00.989883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-02-01T18:39:11.165153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
adj closeclosehighlowopenvolume
adj close1.0001.0000.9980.9980.9960.015
close1.0001.0000.9980.9980.9960.015
high0.9980.9981.0000.9960.9980.027
low0.9980.9980.9961.0000.9980.001
open0.9960.9960.9980.9981.0000.015
volume0.0150.0150.0270.0010.0151.000

Missing values

2026-02-01T18:39:01.462111image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-01T18:39:01.513572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Dateadj closeclosehighlowopenvolume
2010-01-042010-01-041117.6999511117.6999511122.3000491097.0999761117.699951184
2010-01-052010-01-051118.0999761118.0999761126.5000001115.0000001118.09997653
2010-01-062010-01-061135.9000241135.9000241139.1999511120.6999511135.900024363
2010-01-072010-01-071133.0999761133.0999761133.0999761129.1999511133.09997656
2010-01-082010-01-081138.1999511138.1999511138.1999511122.6999511138.19995154
2010-01-112010-01-111150.6999511150.6999511161.1999511143.0000001150.699951177
2010-01-122010-01-121128.9000241128.9000241157.1999511127.1999511128.90002451
2010-01-132010-01-131136.4000241136.4000241136.4000241121.0000001136.40002458
2010-01-142010-01-141142.5999761142.5999761145.9000241132.8000491137.00000081
2010-01-152010-01-151130.0999761130.0999761133.4000241127.1999511132.80004950
Dateadj closeclosehighlowopenvolume
2019-08-132019-08-131502.1999511502.1999511531.4000241483.6999511510.400024672
2019-08-142019-08-141515.9000241515.9000241520.5000001497.0000001500.000000328
2019-08-152019-08-151519.5999761519.5999761522.6999511510.5999761519.80004987
2019-08-162019-08-161512.5000001512.5000001524.5999761504.6999511524.5999761815
2019-08-192019-08-191500.4000241500.4000241507.5999761492.9000241507.199951205
2019-08-202019-08-201504.5999761504.5999761506.0999761497.5000001497.500000486
2019-08-212019-08-211504.5999761504.5999761505.0000001498.8000491504.900024350
2019-08-222019-08-221497.3000491497.3000491497.3000491493.8000491495.099976686
2019-08-232019-08-231526.5999761526.5999761527.5999761493.5000001493.500000983
2019-08-262019-08-261526.3000491526.3000491543.3000491524.3000491543.199951334